Abstract
Air pollution can endanger human health, especially in urban areas. Assessment of air quality primarily relies on ground-based measurements, but these provide only limited information on the spatial distribution of pollutants. In recent years, satellite derived Aerosol Optical Depth (AOD) has been used to approximate particulate matter (PM) with varying success. In this study, the relationship between hourly mean concentrations of particulate matter with a diameter of 10 micrometers or less (PM10) and instantaneous AOD measurements is investigated for Berlin, Germany, for 2001–2015. It is found that the relationship between AOD and PM10 is rarely linear and strongly influenced by ambient relative humidity (RH), boundary layer height (BLH), wind direction and wind speed. Generally, when a moderately dry atmosphere (30% < RH ≤ 50%) coincides with a medium BLH (600–1200 m), AOD and PM10 are in the same range on a semi-quantitative scale. AOD increases with ambient RH, leading to an overestimation of the dry particle concentration near ground. However, this effect can be compensated if a low boundary layer (<600 m) is present, which in turn significantly increases PM10, eventually leading to satellite AOD and PM10 measurements of similar magnitude. Insights of this study potentially influence future efforts to estimate near-ground PM concentrations based on satellite AOD.
Highlights
The adverse health effects of Particulate Matter (PM) on the human respiratory and cardiovascular system are well known and include asthma, emphysema, and lung cancer [1,2,3]
A strong positive linearity would result in a slope of zero, as increasing Aerosol Optical Depth (AOD) would coincide with increasing PM10ranked. The rank of AOD (PM10), resulting in a constant Air Quality Rank Difference Index (AiRDI)
Higher AOD is likely to overestimate PM10 concentrations; AiRDI is more likely to be positive for high AOD, but more likely to be negative for low AOD
Summary
The adverse health effects of Particulate Matter (PM) on the human respiratory and cardiovascular system are well known and include asthma, emphysema, and lung cancer [1,2,3]. Measures to reduce ambient PM concentrations are mandatory in many countries once legal thresholds are exceeded, the most effective approach to reduce PM concentrations is still a matter of debate. One fact that makes it hard for policy makers to choose the right measures is that the processes leading to excessive particulate concentrations in urban regions are not yet fully understood. To better constrain the processes driving PM distribution, extensive and spatially continuous data are required; this information is not readily available. Measurement stations are much more common in urban areas than in rural areas.
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